Streamr Announces DATA Tokens Listed on Bitfinex, the Leading Global Exchange

2. November 2017.
Milestone comes after Streamr’s successful 30 Million CHF Crowd Contribution Period

Zug, Switzerland – November 3, 2017Streamr, the decentralized real-time data economy, today announced that its token called DATAcoin (DATA) has been listed onBitfinex, one of the world’s largest cryptocurrency exchanges. The listing on Bitfinex came into effect at 12 noon UTC, allowing DATAcoin holders trade against BTC, ETH and USD. The announcement follows Streamr’s successful crowd contribution period that rapidly reached its 30 million CHF hard cap.

Streamr CEO and Co-founder Henri Pihkala said: “Bitfinex listing for our token is a significant milestone in achieving our mission to build a decentralized, scalable, and secure data economy. This welcome development showcases the high potential of our project and the boundless possibilities for real-time data tokenization.”

“This is an outstanding first step in our DATAcoin’s journey and is in the best interest of current DATA token holders, and those seeking to join the community. As Streamr begins trading on Bitfinex, with strong industry support and our stellar advisors behind us, we are well positioned to build the best platform imaginable and revolutionize how people and machines view, utilize, and share data,” added Pihkala.

Connecting both producers and consumers, Streamr aims to create a market for real-time data. The Data Market categorizes and showcases publicly available data streams. The Streamr token, DATAcoin, is needed to access and operate the market, and to compensate nodes in the P2P network. Subscribers pay for the data with the token while producers and participants are reimbursed automatically and securely.

Bitfinex will enable margin trading for DATA pairs as the order book develops appropriate liquidity, letting users trade with leverage via funding from the peer-to-peer margin funding platform. Bitfinex has the most liquid order book globally and is one of the most popular marketplaces for digital asset trading, with a current 24-hour volume of over $1 billion USD.

The Streamr crowd contribution period was managed by Bitcoin Suisse, the world’s leading crypto-asset broker and asset manager. Operating on a registration model, interested parties underwent a thorough Know Your Customer (KYC) process prior to whitelisting and participation.

Bitcoin Suisse Head of ICO and Streamr advisor Nicolai Oster said, “Backed by technical expertise, deep industry knowledge, and global experience, Streamr has the potential to not only overhaul existing data systems but to build completely new platforms and networks. Having managed the successful crowd contribution period, Bitcoin Suisse is proud to continue supporting the Streamr team and facilitate the listing of DATA on Bitfinex and on other exchanges.”

In line with the company’s vision for a platform that is fair and open to all, Streamr’s crowd contribution period began on October 12, 2017, with a 24-hour exclusive period for participants contributing 500-5000 CHF. Once closed, the large cap opened for contributions between 5,000 and 50,000 CHF and was full within 90 minutes. The crowd contribution period saw over 1300 contributors participate.

“Every second, volumes of data are generated by sensors and connected devices in a range of sectors and services, and in the coming years, real-time data will increasingly turn into a commodity. It is our objective to lead the way in the tokenization of real-time data through the creation of the Streamr technology stack. With the listing of DATA on Bitfinex, our goal is one step closer to achievement,” concluded Pihkala.

About Streamr:

Streamr, the technology stack for real-time data, aims to tokenize the value in data by enabling a new way for machines and people to trade it on a decentralized P2P network. Founded in 2017 by Henri Pihkala, Nikke Nylund, and Risto Karjalainen, Streamr offers scalable, low-latency, and untamperable data delivery and persistence in an effort to overcome the limitations of traditional centralized real-time data platforms.

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